Overall Statistics
Total Trades
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Net Profit
0%
Sharpe Ratio
0
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
0.87
Tracking Error
0.125
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
# region imports
from AlgorithmImports import *
import math
# endregion

class WellDressedBrownCrocodile(QCAlgorithm):

    def Initialize(self):
        self.SetSecurityInitializer(lambda x: x.SetDataNormalizationMode(DataNormalizationMode.Raw))
        self.SetStartDate(2022, 12, 16)  
        self.SetEndDate(2023, 1, 6)
        self.SetCash(100000)  
        self.fx = self.AddForex("EURUSD", Resolution.Hour)
        self.symbol = self.fx.Symbol

        self.highList = []
        self.lowList = []
        self.highValue = 0
        self.lowValue = 0


        self.pphl = self.PPHL(self.symbol, 10, 10)

        self.Schedule.On(self.DateRules.EveryDay(self.symbol), 
                        self.TimeRules.At(14, 0, 0), self.ValuesTest)



    def ValuesTest(self):
        self.Debug(str(len(self.highList)) + " = length of high list")
        self.Debug(str(len(self.lowList)) + " = length of low list")
        self.Debug(self.highValue)
        self.Debug(str(self.lowValue) + " = low value")


    def OnData(self, slice: Slice) -> None:
        if not self.pphl.IsReady:
            return

        price = self.Securities[self.symbol].Price

        self.highList = self.pphl.GetHighPivotPointsArray()
        if len(self.highList) > 0:
            self.highValue = self.highList[0]

        self.lowList = self.pphl.GetLowPivotPointsArray()
        if len(self.lowList) > 0:
            self.lowValue = self.lowList[0]